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Instructors: Prof. Dr. Peter Kling
Event type:
Lecture
Displayed in timetable as:
MDAE-VL
Hours per week:
4
Language of instruction:
German/English
Min. | Max. participants:
- | 20
Comments/contents:
Algorithmics is the art of problem solving. We are confronted with it in both our everyday life as well as in the buisness world. Examples include simple navigation problems, automatic filtering of the flood of information in the Internet, or compelx optimization problems in the buisness world. As this is a key expertise of any computer scientist, we will get to know several standard methods as well as recent research results from different branches like approximation algorithms, online algorithms, as well as randomized and combinatorial algorithms. This includes both a overview of these topics as well as an in-depth study and mathematical analysis of classical and recent algorithmic results.
Homepage: https://www.inf.uni-hamburg.de/en/inst/ab/tea/teaching/2022-ss/mdae.html
Learning objectives:
- design and analyze provable efficient algorithms
- overview of both classical and current methods in algorithm design
- be able to understand theoretical research papers on algorithmic results
- know the most important tools in current algorithm design
- apply the aquired knowledge to solve new problems
Didactic concept:
The lecture contains an integrated tutorial. Students are expected to prepare exercises at home, whose solutions are to be presented and discussed at the black-/whiteboard. The preparation of the exercises and their presentation/discussion are part of the completed coursework.
The exact schedule and procedure for the seminar of this modul will be discussed during the first lecture. Talks will be scheduled in a dedicated block at the end of the semester.
Literature:
Among others, a selction from:
- different research papers
- Vijay V. Vazirani. 2010. Approximation Algorithms. Springer Publishing Company, Incorporated.
- Allan Borodin and Ran El-Yaniv. 1998. Online Computation and Competitive Analysis. Cambridge University Press, New York, NY, USA.
- Michael Mitzenmacher and Eli Upfal. 2005. Probability and Computing: Randomized Algorithms and Probabilistic Analysis. Cambridge University Press, New York, NY, USA.
- Niv Buchbinder and Joseph (Seffi) Naor. 2009. The Design of Competitive Online Algorithms Via a Primal-Dual Approach. Now publishers Inc.
Additional examination information:
The exam of the modul will most likely take the form of an oral examination. Both the material from the lecture (and the integrated tutorial) as well as from the associated seminar are relevant. If the number of participants is unexpectedly large, we might switch to a written exam. This will be discussed during the first meeting.
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